973 resultados para harmonic approximation


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The voltage ripple and power loss in the DC-capacitor of a voltage source inverter depend on the harmonic currents flowing through the capacitor. This paper presents a double Fourier series based analysis of the harmonic contents of the DC capacitor current in a three-level neutral-point clamped (NPC) inverter, modulated with sine-triangle pulse-width modulation (SPWM) or conventional space vector pulse-width modulation (CSVPWM) schemes. The analytical results are validated experimentally on a 3-kVA three-level inverter prototype. The capacitor current in an NPC inverter has a periodicity of 120(a similar to) at the fundamental or modulation frequency. Hence, this current contains third-harmonic and triplen-frequency components, apart from switching frequency components. The harmonic components vary with modulation index and power factor for both PWM schemes. The third harmonic current decreases with increase in modulation index and also decreases with increase in power factor in case of both PWM methods. In general, the third harmonic content is higher with SPWM than with CSVPWM at a given operating condition. Also, power loss and voltage ripple in the DC capacitor are estimated for both the schemes using the current harmonic spectrum and equivalent series resistance (ESR) of the capacitor.

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The down conversion of radio frequency components around the harmonics of the local oscillator (LO), and its impact on the accuracy of white space detection using integrated spectrum sensors, is studied. We propose an algorithm to mitigate the impact of harmonic downconversion by utilizing multiple parallel downconverters in the system architecture. The proposed algorithm is validated on a test-board using commercially available integrated circuits and a test-chip implemented in a 130-nm CMOS technology. The measured data show that the impact of the harmonic downconversion is closely related to the LO characteristics, and that much of it can be mitigated by the proposed technique.

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Nano-crystals of LiNbxTa1 (-) O-x(3) were evolved by subjecting melt-quenched 1.5Li(2)O-2B(2)O(3)-xNb(2)O(5)-(1 - x)Ta2O5 glasses (where x = 0, 0.25, 0.5, 0.75 and 1.00) to a controlled 3-h isothermal heat treatment between 530 and 560 degrees C. Detailed X-ray diffraction and Raman spectral studies confirmed the formation of nano-crystalline LiNbxTa1 (-) O-x(3) along with a minor phase of ferroelectric and non-linear optic Li2B4O7. The sizes of the nanocrystals evolved in the glass were in the range of 19-37 nm for x = 0-0.75 and 23-45 nm for x = 1.00. Electron microscopic studies confirmed a transformation of the morphology of the nano-crystallites from dendritic star-shaped spherulites for x = 0 to rod-shaped structures for x = 1.00 brought about by a coalescence of crystallites. Broad Maker-fringe patterns (recorded at 532 nm) were obtained by subjecting the heat-treated glass plates to 1064 nm fundamental radiation. However, an effective second order non-linear optic coefficient, d(eff), of 0.45 pm/V, which is nearly 1.2 times the d(36) of KDP single crystal, was obtained for a 560 degrees C/3 h heat-treated glass of the representative composition x = 0.50 comprising 37 nm sized crystallites. (C) 2015 Elsevier B.V. All rights reserved.

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Nano-crystals of LiNbxTa1 (-) O-x(3) were evolved by subjecting melt-quenched 1.5Li(2)O-2B(2)O(3)-xNb(2)O(5)-(1 - x)Ta2O5 glasses (where x = 0, 0.25, 0.5, 0.75 and 1.00) to a controlled 3-h isothermal heat treatment between 530 and 560 degrees C. Detailed X-ray diffraction and Raman spectral studies confirmed the formation of nano-crystalline LiNbxTa1 (-) O-x(3) along with a minor phase of ferroelectric and non-linear optic Li2B4O7. The sizes of the nanocrystals evolved in the glass were in the range of 19-37 nm for x = 0-0.75 and 23-45 nm for x = 1.00. Electron microscopic studies confirmed a transformation of the morphology of the nano-crystallites from dendritic star-shaped spherulites for x = 0 to rod-shaped structures for x = 1.00 brought about by a coalescence of crystallites. Broad Maker-fringe patterns (recorded at 532 nm) were obtained by subjecting the heat-treated glass plates to 1064 nm fundamental radiation. However, an effective second order non-linear optic coefficient, d(eff), of 0.45 pm/V, which is nearly 1.2 times the d(36) of KDP single crystal, was obtained for a 560 degrees C/3 h heat-treated glass of the representative composition x = 0.50 comprising 37 nm sized crystallites. (C) 2015 Elsevier B.V. All rights reserved.

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In this paper, we present two new stochastic approximation algorithms for the problem of quantile estimation. The algorithms uses the characterization of the quantile provided in terms of an optimization problem in 1]. The algorithms take the shape of a stochastic gradient descent which minimizes the optimization problem. Asymptotic convergence of the algorithms to the true quantile is proven using the ODE method. The theoretical results are also supplemented through empirical evidence. The algorithms are shown to provide significant improvement in terms of memory requirement and accuracy.

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A low-order harmonic pulsating torque is a major concern in high-power drives, high-speed drives, and motor drives operating in an overmodulation region. This paper attempts to minimize the low-order harmonic torques in induction motor drives, operated at a low pulse number (i.e., a low ratio of switching frequency to fundamental frequency), through a frequency domain (FD) approach as well as a synchronous reference frame (SRF) based approach. This paper first investigates FD-based approximate elimination of harmonic torque as suggested by classical works. This is then extended into a procedure for minimization of low-order pulsating torque components in the FD, which is independent of machine parameters and mechanical load. Furthermore, an SRF-based optimal pulse width modulation (PWM) method is proposed to minimize the low-order harmonic torques, considering the motor parameters and load torque. The two optimal methods are evaluated and compared with sine-triangle (ST) PWM and selective harmonic elimination (SHE) PWM through simulations and experimental studies on a 3.7-kW induction motor drive. The SRF-based optimal PWM results in marginally better performance than the FD-based one. However, the selection of optimal switching angle for any modulation index (M) takes much longer in case of SRF than in case of the FD-based approach. The FD-based optimal solutions can be used as good starting solutions and/or to reasonably restrict the search space for optimal solutions in the SRF-based approach. Both of the FD-based and SRF-based optimal PWM methods reduce the low-order pulsating torque significantly, compared to ST PWM and SHE PWM, as shown by the simulation and experimental results.

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A two-point closure strategy in mapping closure approximation (MCA) approach is developed for the evolution of the probability density function (PDF) of a scalar advected by stochastic velocity fields. The MCA approach is based on multipoint statistics. We formulate a MCA modeled system using the one-point PDFs and two-point correlations. The MCA models can describe both the evolution of the PDF shape and the rate at which the PDF evolves.

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It is now possible to improve the precision of well survey calculations by order of magnitude with numerical approximation.

Although the most precise method of simulating and calculating a wellbore trajectory generally requires more calculation than other, less-accurate methods, the wider use of computers in oil fields now eliminates this as an obstacle.

The results of various calculations show that there is a deviation of more than 10 m among the different methods of calculation for a directional well of 3,000 m.1 Consequently, it is important to improve the precision and reliability of survey calculation-the fundamental, necessary work of quantitatively monitoring and controlling wellbore trajectories.

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The Mapping Closure Approximation (MCA) approach is developed to describe the statistics of both conserved and reactive scalars in random flows. The statistics include Probability Density Function (PDF), Conditional Dissipation Rate (CDR) and Conditional Laplacian (CL). The statistical quantities are calculated using the MCA and compared with the results of the Direct Numerical Simulation (DNS). The results obtained from the MCA are in agreement with those from the DNS. It is shown that the MCA approach can predict the statistics of reactive scalars in random flows.

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An analytical solution to the three-dimensional scattering and diffraction of plane SV-waves by a saturated hemispherical alluvial valley in elastic half-space is obtained by using Fourier-Bessel series expansion technique. The hemispherical alluvial valley with saturated soil deposits is simulated with Biot's dynamic theory for saturated porous media. The following conclusions based on numerical results can be drawn: (1) there are a significant differences in the seismic response simulation between the previous single-phase models and the present two-phase model; (2) the normalized displacements on the free surface of the alluvial valley depend mainly on the incident wave angles, the dimensionless frequency of the incident SV waves and the porosity of sediments; (3) with the increase of the incident angle, the displacement distributions become more complicated; and the displacements on the free surface of the alluvial valley increase as the porosity of sediments increases.

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This paper is concerned with the ensemble statistics of the response to harmonic excitation of a single dynamic system such as a plate or an acoustic volume. Random point process theory is employed, and various statistical assumptions regarding the system natural frequencies are compared, namely: (i) Poisson natural frequency spacings, (ii) statistically independent Rayleigh natural frequency spacings, and (iii) natural frequency spacings conforming to the Gaussian orthogonal ensemble (GOE). The GOE is found to be the most realistic assumption, and simple formulae are derived for the variance of the energy of the system under either point loading or rain-on-the-roof excitation. The theoretical results are compared favourably with numerical simulations and experimental data for the case of a mass loaded plate. © 2003 Elsevier Ltd. All rights reserved.

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Sequential Monte Carlo methods, also known as particle methods, are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. In many applications it may be necessary to compute the sensitivity, or derivative, of the optimal filter with respect to the static parameters of the state-space model; for instance, in order to obtain maximum likelihood model parameters of interest, or to compute the optimal controller in an optimal control problem. In Poyiadjis et al. [2011] an original particle algorithm to compute the filter derivative was proposed and it was shown using numerical examples that the particle estimate was numerically stable in the sense that it did not deteriorate over time. In this paper we substantiate this claim with a detailed theoretical study. Lp bounds and a central limit theorem for this particle approximation of the filter derivative are presented. It is further shown that under mixing conditions these Lp bounds and the asymptotic variance characterized by the central limit theorem are uniformly bounded with respect to the time index. We demon- strate the performance predicted by theory with several numerical examples. We also use the particle approximation of the filter derivative to perform online maximum likelihood parameter estimation for a stochastic volatility model.